Image signal processing apparatus and digital signal processing method

ABSTRACT

In each conversion blocks  10, 20  and  30 , pixels adjacent to a subject pixel data are selected in the class tap construction section from SD signals, the detection of level distribution pattern of the pixel data is performed in the class categorization section and a class is determined based on the detected pattern. The pixel data of the subject pixel is generated by reading the prediction coefficient corresponding to classes from the prediction coefficient memory and performing prediction operation in the sum of products operation section using pixel data of the selected pixel selected by the prediction tap construction section and the prediction tap selection section and the read prediction coefficient. According to the selection of the switching sections  41  and  42 , a HD signal having a high resolution is obtained and a signal whose tone level of a SD signal is corrected is obtained.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to a digital signal processingapparatus and a digital signal processing method. Particularly, itrelates to the digital signal processing apparatus and method forprocessing an input digital image signal and generating an outputdigital image signal.

[0003] 2. Description of the related art

[0004] Recently, an image display device using a cathode-ray tube as adisplay device has been connected with a variety of digital devices todisplay an image on the display device. On the image display device, theresolution has been also enhanced so that the image display device candisplay an image very finely. Therefore, when a signal output from thedigital device is a SD (Standard Definition) signal corresponding to avideo signal according to NTSC system the SD signal may be convertedinto a HED (High Definition) signal corresponding to a video signal witha high resolution to display an image of high quality and thus convertedsignal may be supplied to the image display device.

[0005] Moreover, as the display device, not only a cathode-ray tube hasbeen used, but also a liquid crystal display panel, plasma display panelor the like has been used for reducing the power consumption, upsizingthe display screen, reducing the space and so forth.

[0006] When types of display devices are different, for example, if a SDsignal is converted into a HD signal and thus converted signal issupplied to the image display device having display device such asliquid crystal display panel, as do the image display device using thecathode-ray tube, this may prevent such image display device havingliquid crystal display panel from displaying an image of high qualitybecause of the difference of the characteristics of display devices.

[0007]FIGS. 1 and 2 respectively show the characteristics of acathode-ray tube and a liquid crystal display element used as a displaydevice. Now, in the case of a cathode-ray tube, as shown in FIG. 1, itis known that the relationship between an input signal and a luminancechanges in proportion to an input signal to the power of γ(=about 2.2).On the other hand, in the case of a liquid crystal display element, asto the relationship between the input signal and the light transparency(luminance), when a signal level of input signal is low or high, thechanging amount of the luminance is little, as shown in FIG. 4. Further,when the signal level is at intermediate level, the luminance largelychanges corresponding to a signal level of the input signal. Therefore,for example, when the input signal is in a range of A or A′, no changesof the input signal appear as the difference of luminance, and thus itsluminance information is missed in the liquid crystal display element.Moreover, in the liquid crystal display element, since strengths ofelectric field applying to a liquid crystal layer are differentdepending upon dispersion of a liquid crystal cell in the direction ofthickness thereof, a dispersion of the luminance may occur. Furthermore,the contrast ratio in a liquid crystal display element is in the orderof a fraction of that of the cathode-ray tube. Therefore, where a liquidcrystal display element is used as a display device, a high qualitydisplay image may be obtained by making up the deficit tone rather thanby enhancing the resolution.

OBJECT AND SUMMARY OF THE INVENTION

[0008] It is accordingly an object of the invention to provide digitalsignal processing apparatus and method capable of displaying an image ofa high quality by enhancing the resolution or by making up the tonecorresponding to a display device for use.

[0009] The present invention relates to a digital signal processingapparatus comprising generating means for generating an output digitalimage signal and control means for controlling the generating means.According to his invention, the generating means is supplied with aninput digital image signal. In accordance with one aspect of theinvention, a plurality of pixel data adjacent to a subject pixel data isselected out of the input digital image signal and clustered to produceeach class. A memory stores predictive operation parameter data forrespective classes at addresses corresponding to the respective classesdetermined by the clustering means. Selecting means selects a pluralityof pixel data corresponding to a pixel data of the output digital imagesignal from the input digital image signal. Predictive operating meansoperates said predictive operation parameter data from said memory andthe plurality of pixel data from said selecting means. The control meanscontrols the generating means such that the generating means selects oneof a plurality of kinds of predictive operation and generates the outputdigital image signal corresponding to the selected kind of predictiveoperation.

[0010] In accordance with another aspect of the invention, a digitalsignal processing method for processing an input digital image signaland generating an output digital image signal is provided. In themethod, a plurality of pixel data of the input digital image signaladjacent to a subject pixel data are clustered to produce each class,and predictive operation parameter data for respective classes is storedat addresses of memory corresponding to the respective classesdetermined by the clustering means. A plurality of pixel data are thenselected from the input digital image signal corresponding to a pixeldata of the output digital image signal. The predictive operationparameter data from the memory and the plurality of pixel data from saidselecting means are operated to produce a plurality of kinds ofpredictive operation of generating means. Further, one of the kinds ofpredictive operation is selected to generate the output digital imagesignal corresponding to the selected kind of predictive operation.

[0011] The conclusion portion of this specification particularly pointsout and distinctly claims the subject matte of the present invention.However those skill in the art will best understand both theorganization and method of operation of the invention, together withfurther advantages and objects thereof, by reading the remainingportions of the specification in view of the accompanying drawing(s)wherein like reference characters refers to like elements.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012]FIG. 1 is a graphical representation showing characteristics ofdisplay device using a cathode-ray tube;

[0013]FIG. 2 is a graphical representation showing characteristics ofdisplay device using a liquid crystal display element;

[0014]FIG. 3 is a block diagram showing a constitution of an embodimentof a digital signal processing apparatus of the present invention;

[0015]FIG. 4 is a block diagram showing a constitution of a classcategorization section shown in FIG. 3;

[0016]FIG. 5 is a block diagram showing a constitution of a predictioncoefficient learning block (resolution conversion);

[0017]FIG. 6 is a block diagram showing a constitution of a predictioncoefficient learning block (tone conversion);

[0018]FIG. 7 is a graphical representation showing a characteristic ofthe filter 71;

[0019]FIGS. 8A and 8B are drawings illustrating a pixel slicing of theresolution conversion block;

[0020]FIG. 9 is a drawing illustrating a pixel slicing of the resolutionconversion block;

[0021]FIG. 10 is a drawing showing the result of a resolutionconversion;

[0022]FIG. 11 is a diagram illustrating a tone conversion operation;

[0023]FIGS. 12A and 12B are graphical representations showing tonelevels of before and after the tone conversion;

[0024]FIGS. 13A through 13C are graphical representations showing aluminance distribution on the screen before and after the toneconversion;

[0025]FIG. 14 is a block diagram showing another embodiment of aconstitution of a digital signal processing apparatus of the presentinvention;

[0026]FIG. 15 is a block diagram showing a constitution of conversionblock 90; and

[0027]FIGS. 16A and 16B are drawings illustrating the selectingoperation of a prediction tap when operation is detected.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] Hereinafter, one embodiment of the present invention will bedescribed with reference to the drawings. In one embodiment, aresolution conversion processing for making up resolution or a toneconversion processing for enhancing a tone is carried out to an inputimage signal, for example, a signal such that a video signal accordingto NTSC system or the like is digitalized (hereinafter, referred to asSD (Standard Definition) signal), by switching them corresponding to thedisplay device employing in an image display device.

[0029] In this resolution conversion processing, the signal having theresolution of image enhanced on the basis of SD signal by performing aclass categorization adaptation (hereinafter, referred to as HDprocessing (High Definition) signal) is generated. Specifically, aninformation memory means for storing a prediction operation settinginformation which has been previously derived from learning per eachclass is provided as well as class division is carried out correspondingto three dimensional (time and space) distribution of a signal level ofa SD signal, the most suitable estimate value is output by performingoperation on the basis of a prediction operation setting informationcorresponding to a class, the number of pixels are made increased in thehorizontal direction and the vertical direction and a HD signal having aresolution higher than that of SD signal is generated.

[0030] Moreover, in the tone conversion processing, a tone of an imageon the basis of a SD signal is enhanced than before the tone conversionby performing a class categorization adaptation processing.Specifically, an information memory means for storing a predictionoperation setting information which has been previously derived fromlearning per each class is provided as well as the most suitableestimate value is output by performing operation on the basis of aprediction operation setting information corresponding to a class, and aSD signal whose tone has been enhanced is generated.

[0031]FIG. 3 shows a constitution of a digital signal processingapparatus with reference to this invention. A luminance data of a SDsignal is supplied to a class tap construction section 11 of aresolution conversion main block 10, a prediction tap constructionsection 13, a class tap construction section 21 of a resolutionconversion sub-block 20, a prediction tap construction section 23, aclass tap 31 of a tone level conversion block 30,and a prediction tapconstruction section 33. It should be noted that the resolutionconversion main block 10 and the resolution conversion sub-block 20 arein a similar constitution, the description of the resolution conversionsub-block 10 is substituted by that of the resolution conversion mainblock 10.

[0032] In the class tap construction section 11 (21), the slicing of theregion of a plurality of pixels on the periphery (hereinafter, referredto as “peripheral pixel for resolution conversion”) of the pixel ofinterest to be prepared is carried out in order to enhance theresolution (hereinafter, referred to as “preparation pixel”), and apixel data within the region is supplied to a class categorizationsection 12 (22) as a space class tap.

[0033] In the class categorization section 12 (22), a pattern of leveldistribution of a space class tap is distinguished and classcategorization is carried out. In this case, in order to prevent thenumber of classes from being enlarged, for example, such a processing isperformed so that an input data of each pixel 8 bits (256 kinds) iscompressed into a space class categorization code of less number ofbits. For example, by employing ADRC (Adaptive Dynamic Range Coding), aspace class categorization code whose number of bits is small can begenerated from space class tap. It should be noted that as informationcompression means, compression means such as DPCM (prediction coding),VQ (vector quantization) or the like except for ADRC may be employed.

[0034] ADRC is an adaptive re-quantization method which has beendeveloped for a high efficient coding for a VTR (Video Tape Recorder),however, a local pattern of a signal level can be efficiently expressedin a short word length, in this embodiment, ADRC is used in thegeneration of a space class categorization code.

[0035]FIG. 4 shows a constitution of a class categorization section 12employing ADRC, shown in FIG. 3. Data of peripheral pixel for resolutionconversion is supplied to a maximum value detection circuit 121, aminimum value detection circuit 122, and a delay circuit 123. In themaximum value detection circuit 121, the maximum value Mx is detectedfrom the sliced luminance data of the peripheral pixel for resolutionconversion and supplied to a subtracter 124. Moreover, in the minimumvalue detection circuit 122, the minimum value MN is detected from thesliced luminance data of peripheral pixel for resolution conversion andsupplied to the subtracters 124 and 125. In the subtracter 124, theminimum value MN is subtracted from the maximum value Mx, a dynamicrange DR is calculated. The calculated dynamic range DR is supplied toan adaptive re-quantization circuit 126.

[0036] In delay circuit 123, a luminance data of pixel is delayed by theportion of the time period that the maximum value detection circuit 121and the minimum value detection circuit 122 are taken in detection,respectively, and supplied to the subtracter 125. In the subtracter 125,the minimum value MN is subtracted from the supplied data, and theobtained subtracted value MS is supplied to the adaptive re-quantizationcircuit 126.

[0037] In the adaptive re-quantization circuit 126, quantization of thesubtracted value MS is performed per each pixel using the predeterminedquantization step width corresponding to a dynamic range DR.Furthermore, data obtained by quantization is parallelized per each unitof pixel slicing by a parallelized circuit 127, and supplied to theprediction tap selection 14 (24) and a prediction coefficient memory 15(35) shown in FIG. 3 as a space class categorization code KM (KS).

[0038] In the prediction tap construction section 13 (23), the region inwhich a plurality of pixels necessary to the prediction operation fromSD signal (hereinafter, referred to this as prediction tap) arecontained is sliced, data of a prediction tap is supplied to theprediction tap selection section 14 (24). In the prediction tapselection section 14 (24), the selection of the pixel supplied from theprediction tap construction section 13 (23) is carried out on the basisof the space class categorization code from the class categorizationsection 12 (22), and the selected pixel data is supplied to a sum ofproducts operation section 16 (26).

[0039] In the prediction coefficient memory 15 (25), the predictioncoefficient obtained by learning the relationship between a SD signaland a HD signal is memorized per each class as prediction operationsetting information. This prediction coefficient is information forconverting a SD signal into a HD signal by linear estimation expression.It should be noted that a method of acquiring a prediction coefficientis described later. Here, when space class categorization code KM (KS)is supplied to the prediction coefficient memory 15 (25), a predictioncoefficient corresponding to this space class categorization code isread and supplied to the sum of products operation section 16 (26).

[0040] In the sum of products operation section 16 (26), operation oflinear combination expression (Expression 1) of prediction tap (pixelvalue) T1, T2 . . . Ti from the prediction tap selection section 14 (24)and prediction coefficient read from the prediction coefficient memory15 (25) w1, w2 . . . wi is performed, thereby calculating pixel datanewly formed.

L1=w1×T1+w2×T2+ . . . +wi×Ti  (1)

[0041] In this way, operation is performed on the basis of a predictioncoefficient and a prediction tap of a class corresponding to a patternof level distribution of a space class tap as well as a predictioncoefficient is previously found per class by learning and stored in theprediction coefficient memory 15 (25) and pixel data of HD signal isgenerated.

[0042] Here, the sum of products operation section 16 outputs data onthe existing line of SD signal, and the sum of products operationsection 26 outputs data on the preparation line located between theexisting lines. At the same time, the sum of products operation sections16 and 26 output pixel data of the number of two fold in the horizontaldirection.

[0043] The pixel data generated in the sum of products operation section26 is supplied to a line doubler 27 as well as the generated pixel datain the sum of products operation section 16 is supplied to a linedoubler 17.

[0044] The line doublers 17 and 27 perform processing of line doublespeed. The sum of products operation sections 16 and 26 generate pixeldata of HD signal from SD signal, however, horizontal cycle of thegenerated pixel data is the same as that of SD signal. Therefore, theline doublers 17 and 27 perform a line double speed processing formaking the horizontal frequency two fold by write and read controlsignal CTM. Data output from the line doubler 27 after the line doublespeed processing is performed is supplied to the terminal b of a signalswitching section 41 as well as data output from the line doubler 17after this line double speed processing is performed is supplied to theterminal (a) of a signal switching section 41.

[0045] The signal switching section 41 switches a movable terminal (c)to a terminal (a) and a terminal (b) in the horizontal cycle of HDsignal on the basis of switching control signal CSA from the controlsection 50 described later. Moreover, in the movable terminal c, theterminal a of the signal switching section 42 is connected, data derivedfrom selecting alternatively data from the line doubler 17 and 27 in ahorizontal cycle, specifically, HD signal whose resolution of SD signalis enhanced is supplied to the terminal (a) of the signal switchingsection 42.

[0046] Next, in the class tap construction section 31 of the toneconversion block 30, the region of the pixel of interest which is apixel correcting a luminance level and a plurality of pixels on theperiphery of the pixel of interest (hereinafter, referred to as“peripheral pixel for tone conversion”) is sliced, the luminance data ofthe pixels within the region is supplied to the class categorizationsection 32.

[0047] In the class categorization section 32, a class categorization isperformed by determining not only the luminance level of pixel ofinterest but also pattern of luminance level of peripheral pixels. Alsoin this class categorization section 32, similar to the classcategorization section 12, the luminance class categorization code isgenerated using ADRC and supplied to the prediction tap selectionsection 34 and the prediction coefficient memory 35 as shown in FIG. 3.

[0048] Here, in the class categorization section 32, for example, theluminance class categorization code corresponding to the luminance levelof the pixel of interest and the luminance class categorization codecorresponding to the distribution pattern of the luminance level on thebasis of the pixel of interest and peripheral pixels for tone conversionare generated, the luminance class categorization code KB is generatedon the basis of these two class categorization codes and supplied to theprediction tap selection section 34 and the prediction coefficientmemory 35.

[0049] In the prediction tap construction section 33, a prediction tapwhich is a pixel for prediction operation is sliced from SD signal, andthe luminance data of this prediction tap is supplied to the predictiontap selection section 34.

[0050] In the prediction tap selection section 34, the selection ofpixel supplied from the prediction tap construction section 33 isperformed on the basis of the luminance class categorization code KBfrom the class categorization section 32, and the luminance data of theselected pixel is supplied to the sum of products operation section 36.

[0051] In the prediction coefficient memory 35, the acquired predictioncoefficient is memorized as prediction operation setting information pereach class by learning the relationship between SD signal of proper tonebefore the correction is carried out and the luminance of an imagedisplayed on the display device. This prediction coefficient isinformation for performing a conversion processing in which signal ismade so that the luminance level of the signal is corrected by thelinear estimation expression and tone level creation of the signal isperformed. It should be noted that a method of acquiring a predictioncoefficient is described later.

[0052] Now, when the luminance class categorization code KB is suppliedto the prediction coefficient memory 35, a prediction coefficientcorresponding to the luminance class categorization code is read andsupplied to the sum of products operation section 36.

[0053] In the sum of products operation section 36, operation of linearcombination expression (Expression 2) of prediction tap (pixel value)T1c, T2c . . . Tic from the prediction tap selection section 34 andprediction coefficient read from the prediction coefficient memory 35w1c, w2c . . . wic is performed, thereby calculating new pixel data ofthe pixel of interest.

G=w1c×T1c+w2c×T2c+ . . . +wic×Tic  (2)

[0054] In this way, operation is performed on the basis of a predictioncoefficient and a prediction tap of class corresponding to the patternof luminance level distribution as well as the prediction coefficient isfound by previously learning per each class and memorized in theprediction coefficient memory 35, and the luminance data of pixel ofinterest is corrected and supplied to the terminal b of the signalswitching section 42.

[0055] In the signal switching section 42, the switching control signalCSB is supplied from the control section 50, and the movable terminal(c) is switched to the side of the terminal (a) or to the side of theterminal (b) by this switching control signal CSB.

[0056] To the control section 50, a processing mode setting switch 51 isconnected, switching control signal CSA and CSB are generatedcorresponding to the switch setting condition of the processing modesetting switch 51, supplied to the signal switching sections 41 and 42,and the resolution conversion or tone level conversion is alternativelyselected. Moreover, in the control section 50, for example, as DVI(Digital Visual Interface) worked out by DDWG (Digital Visual WorkingGroup), the connection of an image display device is detected by a hotplug function, the name of the model of an image display device anddisplay device information such as resolution and the like are obtainedby plug and play realized using the function of DDC (Display DataChannel), and a display device employed in the image display device isdiscriminated. Here, in the control section 50, the determination ofwhether or not the display device is made of cathode-ray tube or aliquid crystal display element or like, and the determination of to whatdegree the resolution is enhanced are performed, either the resolutionconversion or tone level conversion is alternatively selected bygenerating switching control signal CSA and CSB on the basis of thedetermination results and supplied to the signal switching sections 41and 42.

[0057] Next, the preparation (learning) of a prediction coefficient willbe described below. In order to obtain a prediction coefficient bylearning, a student signal is generated from teacher signal DY by filtercorresponding to a display device, teacher signal DY input in the filterand student signal DS output from the function filter are made as a pairfor learning, the preparation of a prediction coefficient is carriedout.

[0058]FIG. 5 shows a constitution of prediction coefficient learningblock for preparing a prediction coefficient necessary for performingresolution conversion. In the filter 61, SD signal is formed byperforming thinning out processing to the HD signal which is teachersignal. For example, the number of pixels in the horizontal directionand vertical direction are made as ½, respectively, SD signal is formedas a student signal.

[0059] A SD signal from the filter 61 is supplied to the classcategorization region slicing section 62 and the prediction tap regionslicing section 65. In the class categorization region slicing section62, the region slicing from the SD signal is performed, pixel datawithin the region is supplied to the class categorization sections 63and 64.

[0060] The class categorization sections 63 and 64 generate the classcategorization code using ADRC similar to the class categorizationsections 12 and 22 in the signal conversion device shown in FIG. 3.Here, in the class categorization section 63, the class categorizationcode related to the data on the line of the SD signal is generated andsupplied to the prediction tap region slicing section 65 and the normalequation adding section 66. Moreover, in the class categorizationsection 64, the class categorization code related to the data betweenlines of SD signals is generated, and supplied to the prediction tapregion slicing section 65 and the normal equation adding section 67.

[0061] In the prediction tap region slicing section 65, the slicing ofthe prediction tap region for preparing the data on the line of a SDsignal is performed on the basis of the class categorization code fromthe class categorization section 63, the data within the region issupplied to the normal equation adding section 66 as a prediction tap.Moreover, the slicing of the prediction tap region for preparing databetween lines of the SD singles is performed on the basis of the classcategorization code from the class categorization section 64, and thedata within the region is supplied to the normal equation adding section67 as a prediction tap.

[0062] In the normal equation adding sections 66 and 67, the normalequation data is generated and supplied to the prediction coefficientdetermination section 68, in the prediction coefficient determinationsection 68, a operation processing is performed using the normalequation data and the prediction coefficient is operated.

[0063] Now, to generalize the description of the operation of theprediction coefficient, the operation of prediction coefficient byutilizing n pixels will be described below. When supposing thatrespective luminance levels of input pixels selected as a prediction tapis x1, . . . xn and a luminance level of output pixel is y, set thelinear estimation equation of n tap by utilizing prediction coefficientsw1, . . . , wn. This is shown in the following expression (3):

y=w1×x1+w2×x2+ . . . +wn×xn  (3)

[0064] As a method of finding prediction coefficients w1, . . . wn inthis expression (3), the solution by method of least squares isconsidered. In this solution, data is collected so that an observationequation of the expression (4) is made by supposing that X is aluminance level of input pixel, W is a prediction coefficient, and Y isa luminance level of output pixel. In this expression (4), m representsthe number of learning data, and n represents the number of predictiontaps as described above. $\begin{matrix}{{{X\quad W} = Y}{Provided},\quad {X = \begin{bmatrix}{x11} & {x12} & \ldots & {x1n} \\{x21} & {x22} & \ldots & {x2n} \\\ldots & \ldots & \ldots & \ldots \\{x\quad {m1}} & {x\quad {m2}} & \ldots & {x\quad m\quad n}\end{bmatrix}},{W = \begin{bmatrix}{w1} \\{w2} \\\ldots \\{w\quad n}\end{bmatrix}},{Y = \begin{bmatrix}{y1} \\{y2} \\\ldots \\{y\quad m}\end{bmatrix}}} & (4)\end{matrix}$

[0065] Next, write a residual equation of the expression (5) based onthe observation equation of the expression (4). $\begin{matrix}{{{X\quad W} = {Y + E}},{Provided},{E = \begin{bmatrix}{e1} \\{e2} \\\ldots \\{e\quad m}\end{bmatrix}}} & (5)\end{matrix}$

[0066] From this expression (5), it is considered that most probablevalue of each prediction coefficient wi is obtained in a case where theconditions making the expression (6) minimum are held. $\begin{matrix}{\sum\limits_{i = 1}^{m}{e\quad i^{2}}} & (6)\end{matrix}$

[0067] Specifically, the conditions of Expression (7) may be considered.$\begin{matrix}{{{{e1}\frac{\partial{e1}}{{\partial w}\quad i}} + {{e2}\frac{\partial{e2}}{{\partial w}\quad i}} + \ldots + {e\quad m\quad \frac{{\partial e}\quad m}{{\partial w}\quad i}}} = {0\left( {{i = 1},2,\ldots \quad,n} \right)}} & (7)\end{matrix}$

[0068] Consider the conditions of n pieces based on i of Expression (7),may calculate w1, . . . , wn satisfying this. Hence, the next expression(8) is obtained from Expression (5), further Expression (9) is obtainedfrom Expression (7) and the next Expression (8). $\begin{matrix}{{\frac{{\partial e}\quad i}{\partial{w1}} = {x\quad {i1}}},{\frac{{\partial e}\quad i}{{\partial w}\quad 2} = {x\quad {i2}}},\ldots \quad,{\frac{{\partial e}\quad i}{{\partial w}\quad n} = {x\quad i\quad {n\left( {{i = 1},2,\ldots \quad,m} \right)}}}} & (8) \\{{{\sum\limits_{i = 1}^{m}{e\quad i\quad x\quad {i1}}} = 0},{{\sum\limits_{i = 1}^{m}{e\quad i\quad x\quad {i2}}} = 0},\ldots \quad,{{\sum\limits_{i = 1}^{m}{e\quad i\quad x\quad i\quad n}} = 0}} & (9)\end{matrix}$

[0069] Then, a normal equation of the next Expression (10) can beobtained from Expression (5) and Expression (9). $\begin{matrix}\left\{ \begin{matrix}\begin{matrix}{{{\left( {\sum\limits_{j = 1}^{m}{x\quad {j1x}\quad {j1}}} \right){w1}} + {\left( {\sum\limits_{j = 1}^{m}{x\quad {j1x}\quad {j2}}} \right)\quad {w2}} + \ldots + {\left( {\sum\limits_{j = 1}^{m}{x\quad {j1x}\quad j\quad n}} \right)\quad w\quad n}} = \left( {\sum\limits_{j = 1}^{m}{x\quad {j1}\quad y\quad i}} \right)} \\{{{\left( {\sum\limits_{j = 1}^{m}{x\quad {j2x}\quad {j1}}} \right){w1}} + {\left( {\sum\limits_{j = 1}^{m}{x\quad {j2x}\quad {j2}}} \right)\quad {w2}} + \ldots + {\left( {\sum\limits_{j = 1}^{m}{x\quad {j2x}\quad j\quad n}} \right)\quad w\quad n}} = \left( {\sum\limits_{j = 1}^{m}{x\quad {j2}\quad y\quad i}} \right)}\end{matrix} \\\ldots \\{{{\left( {\sum\limits_{j = 1}^{m}{x\quad j\quad n\quad x\quad {j1}}} \right){w1}} + {\left( {\sum\limits_{j = 1}^{m}{x\quad j\quad n\quad x\quad {j2}}} \right)\quad {w2}} + \ldots + {\left( {\sum\limits_{j = 1}^{m}{x\quad j\quad n\quad x\quad j\quad n}} \right)\quad w\quad n}} = \left( {\sum\limits_{j = 1}^{m}{x\quad j\quad n\quad y\quad i}} \right)}\end{matrix} \right. & (10)\end{matrix}$

[0070] Since the normal equation of Expression (10) is simultaneousequations in which the number of unknowns is n pieces, most probablevalue of each wi can be found by this Expression. Actually, simultaneousequations are solved by employing general matrix solution such as sweepout method (Gauss-Jordan' method of elimination) or the like.

[0071] The normal equation adding sections 66 and 67 respectivelyperform the addition of the normal equation using class informationsupplied from the class categorization sections 63 and 64, a predictiontap of two pairs supplied from the prediction tap region slicing section65 and a HD signal to be prepared.

[0072] After data input of the number of frames sufficient for learningis terminated, the normal equation adding sections 66 and 67 output thenormal equation data to the prediction coefficient determination section68.

[0073] In the prediction coefficient determination section 68, theoperated prediction coefficient is written in the prediction coefficientmemories 15 and 25 as well as the above-described simultaneous equationsis solved to obtain most probable value of each wi which is a predictioncoefficient.

[0074] Next, FIG. 6 shows a constitution of a prediction coefficientlearning block for preparing a prediction coefficient necessary toperform tone conversion. In the filter 71, a student signal BS is formedby performing conversion of a signal level from teacher signal BY ofcorrect luminance level of tone, and supplied to the classcategorization region slicing section 72 and the prediction tap regionslicing section 73. The teacher signal BY input into this filter 71 andthe student signal BS output from the filter 71 are made as a pair forlearning, the preparation of the prediction coefficient is performed.

[0075] The filter 71 is a filter for converting a signal level of theteacher signal BY so that the overall characteristics of the studentsignal BS and a display device are in a linear shape, for example, whenthe characteristic of the display device is a characteristic as shown inFIG. 2, the student signal DS is generated by correcting the teachersignal BY as shown in FIG. 7 so that the tone level of image can becorrectly reproduced on the screen of the display device making theoverall characteristics as in a linear shape.

[0076] A tone level corrected SD signal from this filter 71 is suppliedto the class categorization region slicing section 72 and the predictiontap region slicing section 75. In the class categorization regionslicing section 72, the region slicing is carried out from the tonelevel corrected SD signal is performed and pixel data within the regionis supplied to the class categorization section 73.

[0077] The class categorization section 73 generates a classcategorization code using ADRC, similar to the class categorizationsection 63 and the like and supplies it to the prediction tap regionslicing section 75 and the normal equation adding section 76. In theprediction tap region slicing section 75, for example, a plurality ofperipheral pixels as a center of the pixel of interest are set on thebasis of a class categorization code as a prediction tap, and suppliedto the normal equation adding section 76.

[0078] In the normal equation adding section 76, normal equation data isgenerated and supplied to the prediction coefficient determinationsection 78, in the prediction coefficient determination section 78, aprediction coefficient is operated by performing operation processingusing the normal equation data. In the normal equation adding section 76and the prediction coefficient determination section 78, the processessimilar to the above-described normal equation adding section 66 and theprediction coefficient determination section 68 are performed, and theprediction coefficient operated in the prediction coefficientdetermination section 68 is written in the prediction coefficient memory35.

[0079] As a result of performing learning described above, in theprediction coefficient memories 15 and 25, the prediction coefficientwhich is used for estimating the data of the pixel prepared capable ofestimating it to reach a value statistically closest to the true valueis to be stored. Moreover, in the prediction coefficient memory 35, theprediction coefficient which is used for estimating the luminance levelof the pixel of interest per each class and capable of estimating it toreach a value statistically closest to the true value is to be stored.

[0080] Moreover, the number of pieces of prediction taps output by theprediction tap region slicing sections 65 and 75 is made larger than thenumber of pieces of prediction taps used in an image signal processingdevice, in the prediction coefficient determination sections 68 and 78,a large number of prediction coefficients are found per each class, theprediction coefficient whose absolute value is larger is in turnselected among these prediction coefficients for use, and each of theselected prediction coefficient is stored in an address positioncorresponding to the prediction coefficient memories 15, 25 and 35,respectively as well.

[0081] Next, operations will be described below. First, when it isdistinguished that not only an image based on a SD signal, but also animage based on a HD signal having a higher resolution than that of a SDsignal is also capable of being displayed, the movable terminal c of thesignal switching section 42 is set on the side of the terminal (a) bycorresponding to a switching control signal CSB as well as a cathode-raytube is used as a display device by the means of the communicationbetween the control section 50 and the image display device. Moreover,the movable terminal (c) of the signal switching section 41 isalternatively switched on the side of the terminal (a) or on the side ofthe terminal (b) in a cycle of a HD signal.

[0082] Now, in the class tap construction section 11 and the predictiontap construction section 13 of the resolution conversion main block 10,a SD signal is sliced to the prepared pixel located nearby the line ofthe SD signal, for example, as shown in FIG. 8A, a pixel located inupward, downward, left and right directions is sliced to the preparedpixel Pma as a peripheral pixel Qa for resolution conversion including atime base direction. It should be noted that the number of sliced pixelsin the class tap construction section 11 and the prediction tapconstruction section 13 may be equal or different.

[0083] In the class tap construction section 11, the data of peripheralpixels for resolution conversion is class-classified as a space classtap, the obtained space class categorization code is supplied to theprediction tap selection section 14 and the prediction coefficientmemory 15.

[0084] In the prediction tap selection section 14, the selection of theprediction taps is carried out based on the space class categorizationcode. For example, when it is indicated by the space classcategorization code that a variation of pixel data level is slight, ifthe region to be selected as a prediction tap is narrow, the differencebetween pixel data operated by the sum of products operation section 16does not appear. Therefore, the prediction tap is selected so that theregion to be selected as a prediction tap is widened, and the differencebetween pixel data is generated.

[0085] In this way, two-fold pixel data nearby the line of a SD signalcan be generated by performing the sum of products operation shown inExpression (1) using a prediction coefficient read from the predictiontap selected in the prediction tap selection section 14 and theprediction coefficient memory 15 based on the space class categorizationcode.

[0086] Similarly, in the class tap construction section 21 and theprediction tap construction section 23 of the resolution conversionsub-block 20, a SD signal is sliced to the prepared pixel Pmb locatedaway from the line of a SD signal. For example, as shown in FIG. 8B,pixels located in the upward, downward, left and right directions withrespect to the prepared pixel are sliced as a peripheral pixel QB forresolution conversion including time base direction, and pixel data oftwo-fold can be generated at the position away from the line of a SDsignal by performing the sum of products operation using a predictiontap and a prediction coefficient selected based on the space classcategorization code obtained by the class categorization Now, pixel datagenerated in the resolution conversion main block 10 is supplied to theline doubler 17 and the pixel data is read at the two-fold frequency ofthe SD signal and pixel data generated in the resolution conversionsub-block 20 is supplied to the line doubler 27, the pixel data is readat the two-fold frequency of the SD signal as well, and further, a HDsignal whose resolution conversion from the movable terminal (c) of thesignal switching section 41 can be obtained by alternatively selectingthe data read from the line doublers 17 and 27 at the horizontalfrequency of a HD signal.

[0087] Moreover, similarly also in the class tap construction section 31and the prediction tap construction section 33 of the tone levelconversion block 30, a SD signal is sliced with respect to the pixel ofinterest performing a tone level conversion. For example, as shown inFIG. 9, the pixel located in the upward, downward, left and rightdirections with respect to the pixel of interest Pmc is sliced as aperipheral pixel Qc for tone level conversion, in the classcategorization section 32, the luminance class categorization code isgenerated, in the prediction tap selection section 34, the selection ofthe prediction tap is performed on the basis of the luminance classcategorization code. For example, when it is indicated that theluminance gradient of an image is mild and a variation of levels isslight by the luminance class categorization code, if the regionselected as a prediction tap is narrow, the difference of the luminancedata operated by the sum of products operation section 36 does notappear. Therefore, the prediction tap is selected so that the region tobe selected as a prediction tap is widened, and specifically, thedifference between pixel data is generated.

[0088] In this way, the luminance data is operated and the luminancedata of the pixel of interest can be corrected by performing the sum ofproducts operation indicated in Expression (2) using a prediction tapselected in the prediction tap selection section 34 and a predictioncoefficient read from the prediction coefficient on the luminance classcategorization code.

[0089] Now, a cathode-ray tube is used as a display device by thesetting condition of the processing mode setting switch 51 or thecommunication between the control section 50 and the image displaydevice, and when it is distinguished that not only an image based on aSD signal but also an image based on a HD signal can be displayed, themovable terminal of the signal switching section 42 is set on the sideof the terminal (a). In this case, as shown in FIG. 10, since a newpixel is generated between the pixels on the basis of SD signal and a HDsignal is output, an image of high resolution can be displayed.

[0090] Moreover, when it is distinguished that a liquid crystal displayelement is used as a display device, the movable terminal (c) of thesignal switching section 42 is set on the side of the terminal (b) bythe switching control signal CSB. In this case, since the luminancelevel of the pixel of interest is adjusted corresponding to theluminance level distribution pattern including the luminance level ofthe pixel of interest and peripheral pixels, for example, as shown inFIG. 11, when the signal level of an input image signal is “3”, thesignal level is converted into any of “20”-“25” corresponding to thepattern of the luminance level distribution including peripheral pixels,when the signal level is “4”, the signal level is converted into any of“26”-“29” corresponding to the pattern. Specifically, in the case whereinput and out put characteristics are linear shape and the tone leveldisplay is carried out as shown in a dotted line of FIG. 12A, sinceinput and output characteristics of the display device is non-linearshape, even if the tone level is missed as shown in a full line, thetone level creation is carried out by the tone conversion processing, asshown in FIG. 12B, the tone level similar to that of the case where theinput and output characteristics is in a linear shape can be made beingheld. Therefore, as shown in FIG. 13 A, even in the case where an imageis blacked and collapsed because the luminance level on the screen issmall and the image can be displayed in a sufficient tone level,conversion of the luminance level is carried out so as to be capable ofobtaining a sufficient tone level, the tone level creation is performedby the luminance level of peripheral pixels, and the luminance level isheightened as in the case of table conversion shown in FIG. 13B,however, the luminance level is heightened as shown in FIG. 13C withoutbeing a flat image whose contrast is slight because of the difference ofthe luminance level is slight, the tone creation is also carried out andthe image can be displayed in a high quality image.

[0091] By the way, in the above-described embodiment, the resolutionconversion main block 10 for performing the resolution conversion andthe resolution conversion sub-block 20 and the tone conversion block 30have been separately provided, however, the resolution conversion mainblock 10 and the resolution conversion sub-block 20 and the toneconversion block 30 are made approximately in the same constitutions.Therefore, one block can be also shared between the resolutionconversion and the tone conversion by memorizing prediction coefficientmemorized in the prediction coefficient memory of the tone conversionblock 30 in the prediction coefficient memory of any one of theresolution conversion main block 10 and the resolution conversionsub-block 20.

[0092]FIG. 14 shows a constitution of an image signal processing deviceconstituted so that operations of the tone conversion block 30 and, forexample, the resolution conversion main block 10 are performed in onecomplex conversion block 80.

[0093] The luminance data of SD signal is supplied to the class tapconstruction section 81 of the complex conversion block 80 and theprediction tap construction section 83. Moreover, the SD signal is alsosupplied to the class tap construction section 21 of the resolutionconversion sub-block 20 and the prediction tap construction section 23via the switch 43. It should be noted that the resolution conversionsub-block 20 is identical with the above-described embodiment and thedescription is omitted.

[0094] In the class tap construction section 81, the region of aplurality of pixels on the periphery is sliced to the prepared pixel onthe basis of the conversion mode setting signal MCT from the controlsection 89 described later, or the region of the pixel of interest andperipheral pixels for tone conversion on the periphery of it correctingthe luminance level, and the data of the pixels within the region issupplied to the class categorization section 82.

[0095] In the class categorization section 82, the level distributionpattern of the pixel of the sliced region is distinguished and classcategorization is carried out. In this class categorization, classcategorization processing is carried out on the basis of the conversionmode setting signal MCT supplied from the control section 89, the classcategorization code is generated and supplied to the prediction tapselection section 84 and the prediction coefficient memory 85.

[0096] In the prediction tap construction section 83, the prediction tapis sliced from the region which has been set and supplied to theprediction tap selection section 84 as well as the setting of the regionincluding the prediction tap from SD signal which is necessary to theprediction operation on the basis of the conversion mode setting signalMCT supplied from the control section 89 is performed, the predictiontap is sliced from the region which has been set and supplied to theprediction tap selection section 84.

[0097] In the prediction tap selection section 84, the selection of theprediction tap supplied from the prediction tap construction section 83is performed and the selected prediction tap is supplied to the sum ofproducts operation section 86.

[0098] In the prediction coefficient memory 85, a prediction coefficientfor the resolution conversion acquired by learning the relationshipbetween a SD signal and a HD signal and a prediction coefficient fortone conversion acquired by learning the relationship between a SDsignal of correct tone before the correction and a luminance of an imagedisplayed by a display device are memorized per each class. Theseprediction coefficients are information for converting a SD signal intoa HD signal by a linear estimation equation and carrying out a tonecreation of a SD signal. Now, when the class categorization code issupplied to the prediction coefficient memory 85, any of a predictioncoefficient for resolution conversion or a prediction coefficient fortone conversion on the basis of the conversion mode setting signal MCTsupplied from the control section 89, a prediction coefficientcorresponding to the class categorization code from the selectedprediction coefficients is read and supplied to the sum of productsoperation section 86.

[0099] In the sum of products operation section 86, data of the preparedpixel is operated or data that tone creation of the pixel of interest iscarried out is operated by performing operation with linear combinationequation using a prediction tap from the prediction tap selectionsection 84, a prediction coefficient read from the predictioncoefficient memory 85.

[0100] Now, the sum of products operation section 86 outputs the pixeldata of the number of two-fold in the horizontal direction as well asdata on the existing line of a SD signal in the case where the data ofthe prepared pixel is operated.

[0101] The pixel data generated in the sum of products section 86 issupplied to the line doubler 87. In the line doubler 87, the write andread control signal CTM is supplied from the control section 89, datasupplied from the sum of products operation section 86 is read at thehorizontal frequency or for example, at the two fold frequency of a SDsignal by this write and read control signal CTM, supplied on the sideof the terminal (a) of the signal switching section 45. Moreover, on theside of the terminal (b) of the signal switching section 45, a signaloutput from the line doubler 27 is supplied. In this signal switchingsection 45, the switching control signal CSC is supplied from thecontrol section 89, the movable terminal (c) is switched on the side ofthe terminal (a) or on the side of the terminal (b) by this switchingcontrol signal CSC.

[0102] In the switch 43, the conversion mode setting signal MCT issupplied from the control section 89, the switching operation iscontrolled on the basis of the conversion mode setting signal MCT.

[0103] In the control section 89, display device information is obtainedby communication with an image display device, the display device usedin the image display device is distinguished. Now, in the controlsection 89, if the display device is of a cathode-ray tube, of a liquidcrystal display element or the like, and to what degree the resolutionis are distinguished on the basis of the obtained display deviceinformation, the conversion mode setting signal MCT, the write and readcontrol signal CTM and the switching control signal CTC are generated,supplied to the complex conversion block 80, the switch 43, the linedoublers 27 and 87 and the signal switching section 45 on the basis ofthe determination results, and the resolution conversion or the toneconversion is carried out corresponding to the display device.

[0104] Now, in the control section 89, when it has been distinguishedthat a display device is, for example, of a cathode-ray tube, and of animage display based on a HD signal, the switch 43 is in an on-state bythe conversion mode setting signal. Moreover, in the class tapconstruction section 81, the region of the peripheral pixels forresolution conversion is sliced similarly to the class tap constructionsection 11, in the class categorization section 82, similarly to theclass categorization section 12, the level distribution pattern of thepixel of the sliced region is distinguished and class categorization iscarried out as well.

[0105] In the prediction tap construction section 83, similarly to theprediction tap construction section 13, the setting of the regionincluding the prediction tap from a SD signal necessary to theprediction operation, a prediction tap selection section 84 is slicedfrom the region which has been set, the prediction tap is sliced fromthe region which has been set and supplied to the prediction tapselected. Furthermore, in the prediction tap selection section 84, theselection of the prediction tap supplied from the prediction tapconstruction section 83 on the basis of the class categorization codesimilarly to the prediction tap selection section 14, and the selectedprediction tap is supplied to the sum of products operation section 86.

[0106] Moreover, in the prediction coefficient memory 85, a predictioncoefficient corresponding to the class categorization code is read fromthe prediction coefficient for resolution conversion.

[0107] In the sum of products operation section 86, similarly to the sumof products operation section 16, the operation is performed by linearcombination equation using the prediction tap from the prediction tapselection section 84 and the prediction coefficient read from theprediction coefficient memory 85, thereby calculating data of pixelnewly generated and supplying it to the line doubler 87.

[0108] Now, for example, the sum of products operation section 86outputs the data on the existing line of a SD signal, the sum ofproducts operation section 26 outputs the data on the prepared linelocated between the existing lines as well. Furthermore, the sum ofproducts operation sections 26 and 86 output the pixel data of thenumber of two-fold in the horizontal direction.

[0109] In the line doublers 27 and 87, the line double speed processingis performed on the basis of the write and read control signal CTM, theline double speed processing is performed and the data output from theline doubler 87 is supplied to the terminal (a) of the signal switchingsection 45 as well as the data output from the line doubler 27 issupplied to the terminal (b) of the signal switching section 45.

[0110] In the signal switching section 45, the movable terminal (c) isalternatively switched to the terminal (a) and the terminal (b) in thehorizontal cycle of a HD signal by a switching control signal CSC, andHD signal having a highly enhanced resolution of a SD signal can be madeoutput from the movable terminal (c) of the signal switching section 45.

[0111] Moreover, in the control section 89, when it is distinguishedthat a display device is, for example, of a liquid crystal displayelement by the communication with an image display device, the switch 43is in an off-state by a conversion mode setting signal. Moreover, in theclass tap construction section 81, similarly to the class tapconstructions section 31, the region of peripheral pixel for toneconversion is sliced, in the class categorization section 82, similarlyto the class categorization section 32, the level distribution patternof the pixel of the sliced region is distinguished and classcategorization is carried out as well.

[0112] In the prediction tap construction section 83, similarly to theprediction tap construction section 33, the region including theprediction tap necessary to the prediction operation from the SD signalis set, the prediction tap is sliced from the region which has been set,and supplied to the prediction tap selection section 84. Furthermore, inthe prediction tap selection section 84, similarly to the prediction tapselection section 34, based on the class categorization code, theselection of the prediction tap supplied from the prediction tapconstruction section 83 is performed, and the selected prediction tap issupplied to the sum of products operation section 86.

[0113] Moreover, in the prediction coefficient memory 85, the predictioncoefficient corresponding to the class categorization code is read fromthe prediction coefficients for the tone conversion, supplied to the sumof products operation section 86.

[0114] In the sum of products operation section 86, similarly to the sumof products operation section 36, the operation by linear combinationequation using the prediction tap from the prediction tap selectionsection 84 and the prediction coefficient read from the predictioncoefficient memory 85, thereby generating a new data of the pixel ofinterest and the supplying to the line doubler 87.

[0115] In the line doubler 87, the data is supplied to the terminal (b)of the signal switching section 45 as data of a SD signal withoutperforming line double processing of the supplied data on the basis ofthe write and read control signal CTM. Moreover, in the signal switchingsection 45, it is held in a state that the movable terminal (c) isswitched on the side of the terminal (a) on the basis of the switchingsignal CSC. Therefore, the tone creation is performed, and from themovable terminal (c) of the signal switching section 45, a SD signalwhich is enhanced in tone can be made output.

[0116] In this way, since one conversion block can be shared between theresolution conversion and the tone conversion, the constitution can besimplified.

[0117] Moreover, in the above-described embodiment, when the resolutionconversion and the tone conversion are performed, operation amount isclass-classified, the class categorization code is generated using thiscategorization results, and the selection of the prediction tap and readof the prediction coefficient may be performed in consideration of theoperation amount of an image as proposed in the specification and thedrawings of Japanese Unexamined Patent Publication No. Hei 9-74543gazette applied by the present applicant.

[0118]FIG. 15 shows a constitution of a conversion block still furtherin consideration of an operation amount of an image. In the class tapconstruction section 91 of the conversion block 90, the region ofperipheral pixels for the resolution conversion or peripheral pixels fortone conversion is sliced, and the data of pixel within the region issupplied to the class categorization section 92.

[0119] In the class categorization section 92, the pattern of the leveldistribution is distinguished and class categorization is performed. Inthis class categorization section 32, as described above, for example,using ADRC, the class categorization code is generated and supplied tothe prediction tap selection section 94 and the prediction coefficientmemory 95.

[0120] In the prediction tap construction section 93, the prediction tapis sliced from SD signal and supplied to the prediction tap selectionsection 94. Moreover, in the prediction tap selection section 94, theselection of the pixels supplied from the prediction tap constructionsection 93 is carried out on the basis of the class categorization codefrom the class categorization section 92, and the data of the selectedpixels is supplied to the sum of products operation section 96.

[0121] In the prediction coefficient memory 95, the predictioncoefficient acquired by previously learning is memorized per each class,the prediction coefficient is read corresponding to the classcategorization code and supplied to the sum of products operationsection 96.

[0122] In the sum of products operation section 96, the sum of productsoperation between the prediction tap from the prediction tap selectionsection 94 and the prediction coefficient read from the predictioncoefficient memory 95 is performed, and a new data is operated.

[0123] Now, in the region slicing section 97, in order to classify anamount of operation in a degree into classes, the slicing of a signal isperformed from a SD signal making the prepared pixel and the pixel ofinterest as a reference. Here, the data of sliced pixels is supplied toan operation class categorization section 98. In the operation classcategorization section 98, for example, interframe differential isoperated using the pixel data of the sliced region, and an operationclass code is generated by comparing the average value of its absolutevalues with threshold. This operation class code is supplied to theclass tap construction section 91, and the class tap is slicedcorresponding to the operation class code. Alternatively, the operationclass code is supplied to the class categorization section 92, the finalclass code is generated from the class code on the basis of theoperation class code and the class tap, and supplied to the predictiontap selection section 94 and the prediction coefficient memory 95.Further alternatively, the operation class code is supplied to theprediction tap selection section 94, and the selection of the predictiontap may be performed still further in consideration of the operationclass code.

[0124] For example, when it is distinguished that the size of theoperation is small by the operation class code, it is effective to usethe pixels in the number of two fields portion or more than that.Therefore, as shown in FIG. 16A, the prediction tap Taa is selected withrespect to the prepared pixel Pma. Moreover, when it is distinguishedthat the size of the operation is large by the operation class code, itis effective to use the pixels within one field. Therefore, as shown inFIG. 16B, the prediction tap Tab is selected with respect to theprepared pixel Pmab.

[0125] The sum of products operation is performed using the predictiontap thus selected and the prediction coefficient, thereby being capableof performing the resolution conversion processing corresponding to theoperation of an image. Moreover, also in the tone conversion processing,the tone creation can be also carried out using the operation class codeof an image.

[0126] Moreover, in the case of the above-described, the predictioncoefficient used for linear combination equation of Expression (1) ismemorized as a prediction operation setting information, however, themost suitable estimation equation is memorized per each class and theresolution conversion and the tone conversion processes with more higherprecision can be carried out by operating using the estimation equationof the determined class and the prediction coefficient.

[0127] Furthermore, the prediction operation setting information is madeprovided per each display device, the most suitable resolutionconversion and tone conversion processes corresponding to a variety ofdisplay devices can be carried out in the case where not only theresolution conversion and the tone conversion processes are switched butalso the prediction operation setting information corresponding to thedisplay device is selectable on the basis of the determination resultsof the display device based on the switch setting corresponding to adisplay device or the communication with an image display device asdescribed above.

[0128] It should be noted that concerning with color signal data, it maybe processed similarly to the luminance data, and as proposed in thespecification and the drawings of Japanese Unexamined Patent PublicationNo. Hei 10-229565 gazette applied by the present applicant, a simpleinterpolation processing different from the luminance data may beperformed, for example, an interpolation processing may be performed byoperation processing using the color signal data of the lines locatedupper and lower of the field identical with that of the color signaldata on the lines of the pixel of interest.

[0129] According to the present invention, the pixels on the peripheryof the pixel of interest are selected from the input image signals, thelevel distribution pattern detection of the selected pixel data isperformed, and class is determined based on the detected pattern, thepixel data of the foregoing subject pixel is generated by performing theprediction operation using the prediction coefficient corresponding tothe foregoing determined class and the pixel data of the selected pixelcorresponding to the foregoing subject pixel from the foregoing inputimage signal, and the resolution conversion processing for setting thepixel of the foregoing input image signal and a newly prepared pixel asthe foregoing subject pixel and generating an image signal having ahigher resolution than that of input image signal and the tone levelconversion processing for setting the pixel of the foregoing input imagesignal as the foregoing subject pixel and generating the image signalwhose tone level of the input image signal is corrected arealternatively carried out. Therefore, the resolution conversionprocessing and the tone level conversion processing can be efficientlycarried out by one image signal processing device.

[0130] Moreover, since the prediction coefficient output correspondingto the selection of the pixels, the class determination and classthereof can be switched in the resolution conversion processing and thetone level conversion processing, a high quality image can be displayed.

[0131] Furthermore, the determination of an image display deviceperforming an image display is performed, on the basis of thedetermination results, the resolution conversion processing or the tonelevel conversion processing is performed. Therefore, an image can bedisplayed in a high quality image corresponding to an image displaydevice.

[0132] It will also be appreciated that, although a limited numberembodiments of the invention have been described in detail for purposesof illustration, various modifications may be made without departingfrom the spirit and scope of the invention. Accordingly, the inventionshould not be limited except as by the appended claims.

What is claimed is:
 1. A digital signal processing apparatus forprocessing an input digital image signal and generating an outputdigital image signal, comprising: generating means for generating theoutput digital image signal, said means being supplied with said inputdigital image signal and having means for clustering a plurality ofpixel data of said input digital image signal adjacent to a subjectpixel data to produce a class, a memory for storing predictive operationparameter data for respective classes at addresses corresponding to saidrespective classes determined by said clustering means, means forselecting a plurality of pixel data from said input digital image signalcorresponding to a pixel data of said output digital image signal, andpredictive operating means for operating said predictive operationparameter data from said memory and said plurality of pixel data fromsaid selecting means; and control means for controlling said generatingmeans such that said generating means selects one of a plurality ofkinds of predictive operation and generates the output digital imagesignal corresponding to the selected kind of predictive operation. 2.The digital signal processing apparatus according to the claim 1,wherein said generating means includes first generating meanscorresponding to a first kind of predictive operation and secondgenerating means corresponding to a second kind of predictive operation,and wherein said control means controls said first and second generatingmeans so as to select their outputs.
 3. The digital signal processingapparatus according to the claim 1, wherein said control means controlssaid clustering means and said selecting means so as to select one ofthe kinds of predictive operation.
 4. The digital signal processingapparatus according to the claim 1, wherein said plurality of kinds ofpredictive operation include resolution conversions and tone conversion.5. The digital signal processing apparatus according to the claim 1,wherein said control means controls the generating means based on a typeof display device to be connected with said output digital image signal.6. A digital signal processing method for processing an input digitalimage signal and generating an output digital image signal, comprisingthe steps of: clustering a plurality of pixel data of said input digitalimage signal adjacent to a subject pixel data by clustering means toproduce a class; storing predictive operation parameter data forrespective classes at addresses of memory corresponding to saidrespective classes determined by said clustering means; selecting aplurality of pixel data from said input digital image signalcorresponding to a pixel data of said output digital image signal byselecting means; operating said predictive operation parameter data fromsaid memory and said plurality of pixel data from said selecting meansto produce a plurality of kinds of predictive operation of generatingmeans; and selecting one of said kinds of predictive operation togenerate the output digital image signal corresponding to the selectedkind of predictive operation.
 7. A digital signal processing method forprocessing an input digital image signal and generating an outputdigital image signal, comprising the steps of: clustering a plurality offirst pixel data of said input digital image signal adjacent to asubject pixel data by first clustering means to produce a first class;storing first predictive operation parameter data for the first class ataddress of first memory corresponding to said first class determined bysaid first clustering means; selecting a plurality of first pixel datafrom said input digital image signal corresponding to first pixel dataof said output digital image signal by first selecting means; operatingsaid first predictive operation parameter data from said first memoryand said plurality of first pixel data from said selecting means toproduce a plurality of kinds of first predictive operation of firstgenerating means; clustering a plurality of second pixel data of saidinput digital image signal adjacent to said subject pixel data by secondclustering means to produce a second class; storing second predictiveoperation parameter data for the second class at address of secondmemory corresponding to said second class determined by said secondclustering means; selecting a plurality of second pixel data from saidinput digital image signal corresponding to second pixel data of saidoutput digital image signal by second selecting means; operating saidsecond predictive operation parameter data from said second memory andsaid plurality of second pixel data from said second selecting means toproduce a plurality of kinds of second predictive operation of secondgenerating means; and controlling said first and second generating meansso as to select one of the plurality of kinds of first and secondpredictive operation of first and second generating means as theiroutputs.
 8. The digital signal processing method according to the claim6, further comprising the step of controlling said clustering means andsaid selecting means so as to select one of the kinds of predictiveoperations.
 9. The digital signal processing method according to theclaim 6, wherein said plurality of kinds of operation includesresolution conversion and tone conversion.
 10. The digital signalprocessing method according to the claim 6, further comprising the stepof controlling said generating means based on a type of display deviceto be connected with said output digital image signal.